Digital receiver techniques in radar detectors

ABSTRACT

A method and apparatus are provided for detecting a RADAR signal. RADAR channel data in a frequency range is received, where the frequency range is divided into a plurality of equally wide channels. The received RADAR channel data is digitally processed and analyzed to identify a signal in the RADAR channel data in the frequency range. The frequency range is advanced to a next channel of the plurality of channels, where the frequency range of the next channel of the plurality of channels is non-sequential with the frequency range of the first channel. The steps of receiving, processing, and analyzing are repeated for the next channel of the plurality of channels.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.14/665,585 filed Mar. 23, 2015, which will issue as U.S. Pat. No.9,557,408 on Jan. 31, 2017, which is a divisional of U.S. applicationSer. No. 12/881,729 filed Sep. 14, 2010, issued as U.S. Pat. No.8,988,272 on Mar. 24, 2015, which is a continuation-in-part of U.S.application Ser. No. 12/749,728 filed Mar. 30, 2010, now abandoned; thedisclosures of each of these prior applications are incorporated byreference herein.

FIELD OF THE INVENTION

The present invention relates to radar detectors, and more particularlyto radar detectors which detect police radar signals before the vehicleis within the detection range of the police radar unit.

BACKGROUND OF THE INVENTION

RADAR detectors warn drivers of the use of police RADAR, and thepotential for traffic citations if the driver exceeds the speed limit.The FCC has allocated several regions of the electromagnetic spectrumfor police RADAR use. The bands used by police RADAR are generally knownas the X, K and Ka bands. Each relates to a different part of thespectrum. The X and K bands are relatively narrow frequency ranges,whereas the Ka band is a relatively wide range of frequencies. By theearly 1990's, police RADAR evolved to the point that it could operatealmost anywhere in the 2,600 megahertz wide Ka band. During that timeRADAR detectors kept pace with models that included descriptive nameslike “Ultra Wide” and “Super Wide.” More recently, police have begun touse laser (optical) systems for detecting speed. This technology wastermed LIDAR for “light Detection and Ranging.”

Unlike LIDAR, police RADAR directly determines a vehicle's speed bymeasuring the doppler shift in its returned frequency (such as theincreasing or decreasing pitch of an approaching or receding train oremergency vehicle). Instant-on or pulsed low-powered RADAR has been inuse for many years. For some time to come, this will likely constitutethe greatest occurrence in any area that has not already switchedexclusively to police laser speed enforcement. Most contemporary policeRADAR guns operate on the wide Ka-band RADAR. K-band RADAR still isextremely common, given it historical advantage to Ka RADAR. X-band isalso still widely deployed in some areas, however, newer digital (DSP)police RADAR guns are steadily coming on-line which operate primarily onthe newer Ka band.

RADAR detectors typically comprise a microwave receiver and detectioncircuitry that is typically realized with a microprocessor or digitalsignal processor (“DSP”). Microwave receivers are generally capable ofdetecting microwave components in the X, K, and very broad Ka band. Invarious solutions, either a microprocessor or DSP is used to makedecisions about the signal communicated from the microwave receiver.Systems including a digital signal processor have been shown to providesuperior performance over solutions based on conventionalmicroprocessors due to the DSP's ability to rapidly find and distinguishsignals that are buried in noise.

The DSP or microprocessor in a contemporary RADAR detector isprogrammable. Accordingly, they can be instructed to manage all of theuser interface features such as input switches, lights, sounds, as wellas generate control and timing signals for the microwave receiver and/ora laser detector. Early in the evolution of the RADAR detector,consumers sought products that offered a better way to manage theaudible volume and duration of warning signals. Good examples of thesesolutions are found in U.S. Pat. Nos. 4,631,542, 5,164,729, 5,250,951,and 5,300,932, each of which is hereby incorporated by reference, whichprovide methods for conditioning the response generate by the radardetector.

However, these and other radar detectors still typically have an analogbasic detection method, usually involving an FM demodulator. Theresultant analog signal is then processed by a digital microcontroller.A problem with using an analog detection technique is that the analogdetection has a slow response time. Since a detector must scan a widerange of frequencies in search of radar signals, scan speed is animportant aspect of the detector. Unfortunately, analog detectionmethods involving FM demodulators only allow detectors to look at anarrow frequency bands at specific times, in order to achieve goodsensitivity to RADAR signals over any noise. The narrow bands may assistin the problem that many detectors have been faced with; namely, theirinability to detect short pulsed radar signals, which may occur at anyfrequency in the X, K or Ka bands. In other words, it has become moredifficult to achieve a good compromise between response time andsensitivity using narrow-band analog detection methods. This problem hasbecome even more apparent lately as more RADAR guns have started toimplement short pulsed sources, known as POP-mode RADAR.

The idea behind POP-mode RADAR is simple in principle. If a RADAR guntransmits a sole pulsed RADAR wave, and that transmission only lasts 67ms, conventional RADAR detectors won't likely spot the RADAR beam ofsuch short duration as they are busy sweeping (scanning) multiple bandswithin the X, K, and Ka bands. While the 67 ms version of POP-mode RADARhas essentially been mitigated by most of the major contemporarydetector manufacturers, even quicker versions of POP-mode RADAR havebeen introduced having pulse durations of 16 ms. Even the top of theline models of the contemporary detectors struggle with identifying thisshorter duration POP-mode and the detector only alerts to the pulsedwaves about one out of every 10 bursts.

Therefore there is a need in the art for a RADAR detector that is ableto sweep multiple bands with sufficient speed and sensitivity to be ableto detect POP-mode and other short duration bursts.

SUMMARY OF THE INVENTION

Embodiments of the invention provide a method of detecting RADARsignals. RADAR channel data in a frequency range is received, where thefrequency range may be divided into a plurality of equally widechannels. The received RADAR channel data is digitally processed andanalyzed to identify a signal in the RADAR channel data in the frequencyrange. The frequency range is advanced to a next channel of theplurality of channels, where the frequency range of the next channel ofthe plurality of channels may be nonsequential with the frequency rangeof the first channel. The steps of receiving, processing, and analyzingmay then be repeated for the next channel of the plurality of channels.

In some embodiments, digitally processing the received RADAR channeldata includes concurrently averaging digitally converted samples of theRADAR channel data with digitally converted samples from previouslyreceived RADAR channel data. The concurrent averaging may be performedin parallel utilizing multiple averaging engines.

In some embodiments, analyzing the processed channel data to identify asignal in the RADAR channel data in the frequency range includescomparing samples to a predetermined threshold. The threshold may be adynamic self-adapting threshold, where the threshold adapts tocompensate for temperature variations.

In some embodiments, a pseudo-random channel pattern may be utilized foradvancing to the next channel of the plurality of channels. In otherembodiments, the next channel of the plurality of channels may berandomly selected from the plurality of channels. In these embodiments,statistical analysis may be employed to determine a number of times achannel of the plurality of channels has been analyzed to ensure eachchannel of the plurality of channels may be periodically analyzed.

Embodiments of the invention additionally provide an apparatus fordetecting RADAR signals. The apparatus includes a receiver, a processor,and an averager module. The processor is in communication with thereceiver and the averager module. The processor is configured to receivevia the receiver RADAR channel data in a frequency range. The frequencyrange is divided into a plurality of equally wide channels. Theprocessor may then digitally process the received RADAR channel data andanalyze the processed channel data to identify a signal in the RADARchannel data in the frequency range. The processor advances thefrequency range to a next channel of the plurality of channels, wherethe frequency range of the next channel of the plurality of channels isnonsequential with the frequency range of the first channel. Theprocessor then repeats the steps of receiving, processing, and analyzingfor the next channel of the plurality of channels.

In some embodiments, the receiver includes a RF antenna, a plurality oflocal oscillators, and a band pass filter. The plurality of localoscillators selects bands of frequency in the frequency range undercontrol of the processor.

In some embodiments, the processor digitally processes the receivedRADAR channel data by concurrently averaging in the averager moduledigitally converted samples of the RADAR channel data with digitallyconverted samples from previously received RADAR channel data. Theconcurrent averaging may be performed in parallel utilizing multipleaveraging engines within the averager module.

In some embodiments, the processor may be configured to analyze theprocessed channel data to identify a signal in the RADAR channel data inthe frequency range by comparing samples to a predetermined threshold.The threshold in these embodiments may be a dynamic self-adaptingthreshold, where the processor may be configured to adapt the thresholdto compensate for temperature variations.

In some embodiments, a pseudo-random channel pattern is utilized by theprocessor for advancing to the next channel of the plurality ofchannels. In other embodiments, the next channel of the plurality ofchannels is randomly selected by the processor from the plurality ofchannels. In these embodiments, the processor may statistically analyzea number of times a channel of the plurality of channels has beenanalyzed to ensure each channel of the plurality of channels isperiodically analyzed.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of this specification, illustrate embodiments of the invention and,together with a general description of the invention given above, andthe detailed description given below, serve to explain the invention.

FIG. 1 is an illustration of a vehicle receiving RADAR signals from apolice RADAR.

FIG. 2 is a block diagram of a RADAR detection circuit consistent withembodiments of the invention.

FIG. 3 is a flowchart illustrating digital processing for the RADARdetection circuit of FIG. 2.

FIG. 4 is a graph of sample frequency response data.

FIG. 5 is a detailed block diagram of the digital receiving portion ofFIG. 2 with a noise input source.

FIG. 6 is a graph of an averaged noise floor.

FIGS. 7A-7C are frequency plots of noise frequency data over differentaverage configurations.

FIGS. 8A-8C are corresponding histogram plots for the frequency plots inFIGS. 7A-7C.

FIG. 9 is a table of the percentage of samples found within an amplituderange vs. the number of averages.

FIG. 10 is a table summarizing the factors that affect final sensitivityof the detector system.

It should be understood that the appended drawings are not necessarilyto scale, presenting a somewhat simplified representation of variousfeatures illustrative of the basic principles of the invention. Thespecific design features of the sequence of operations as disclosedherein, including, for example, specific dimensions, orientations,locations, and shapes of various illustrated components, will bedetermined in part by the particular intended application and useenvironment. Certain features of the illustrated embodiments have beenenlarged or distorted relative to others to facilitate visualization andclear understanding. In particular, thin features may be thickened, forexample, for clarity or illustration.

DETAILED DESCRIPTION OF THE INVENTION

Embodiments of the invention implement direct IF sampling techniques.This method does not involve an FM demodulator. An intermediatefrequency of the detector may be digitized by a wide bandanalog-to-digital converter and the resulting digital stream of data maythen be processed completely in the digital domain, making theembodiments truly digital radar detectors. Embodiments employing digitaltechniques also realize, through wide band digital sampling, asignificant improvement in response time, as well as increase insensitivity.

Referring now to FIG. 1, a vehicle 10 is illustrated in operation on aroadway, under exposure to radio frequency signals from a variety ofsources including police sources, such as RADAR gun 12, as well as othernon-police sources of interference from surrounding businesses, homes,etc. (not shown). Vehicle 10 is equipped with a RADAR detector capableof detecting both the police and non-police sources. In someembodiments, the RADAR detector may also be able to identify the presentcoordinate and/or velocity of the vehicle, e.g. using an associated GPSreceiver or alternatively receive of land-based signals such as LORAN,as disclosed in U.S. Pat. No. 6,670,905 of the present assignee, whichis hereby incorporated by reference in its entirety. In theseembodiments, the RADAR detector is able to use this information toenhance its decision-making abilities.

The RADAR detector 14, as illustrated in FIG. 2, includes a processor 16for controlling all functions of the detector 14. Processor 16 receivesinformation on RADAR signals from a microwave receiver 26. In someembodiments, and as seen in FIG. 2, three Local Oscillators, 20, 22, 24are part of a super heterodyne receiver structure 26. Signals from eachlocal oscillator 20, 22, 24 drives a mixer 28, 30, 32 which downconvertsincoming signal to an intermediate frequency for ease of processing. Ateach stage, the mixer 28, 30, 32 creates a copy of the incoming signalat the frequency set by the difference between the original and the LO20, 22, 24 frequencies. Signals from the first two stages are amplifiedby amplifiers 34, 36 before being transmitted to the next stage. Incontemporary detectors, the first local oscillator 20 is typicallycontrolled using analog methods by applying a ramp control voltage, inorder to implement a frequency sweep.

In the embodiment in FIG. 2, a triple-conversion super heterodynereceiver 26 is used to assist in providing greater ability to implementnecessary gain and selectivity as well as to avoid spurious products byproperly selecting frequencies for the oscillators, although, one ofordinary skill in the art will recognize that other numbers ofoscillators, mixers, and amplifiers may also be used. The frequencyshifted input from the super heterodyne receiver 26 is then sent througha band pass filter 38, the bandwidth of which may be chosen based on anumber of steps through the frequency range of interest. The frequenciesof the first and second LOs 20, 22 are changed in steps by processor 16.At each step, the portion of bandwidth, also referred to herein as achannel, is digitized by the analog-to-digital converter (ADC) 40 andprocessed by the FFT 42 and Averager 44 modules under direction of theprocessor 16. By using the FFT 42, all signal processing, detection andrecognition implemented in detector 14 may be performed digitally and inthe frequency domain. After processing, the processor 16 changes thefirst and second LOs 20, 22 to the frequency corresponding to the nextchannel and the process repeats.

In some embodiments, the FFT 42, Averager 44, and processor 16 may beimplemented on a FPGA 46 or ASIC. In other embodiments, thesescomponents may be integral in the processor or implemented as separatehardware components. By using an FPGA 46, as opposed to a conventionalDSP processor, improved digital processing throughput may be realized ata lower cost. Additionally, an FPGA 46 allows for implementation ofseveral digital functions executing in parallel, such as, for examplethe Averager 44. The ability to parallel process may assist in realizingreduced times when running multiple concurrent averaging engines, whichprocess the same signals during averaging. In some embodiments,processor 16 may further be programmed to manage and report detectedsignals in various ways depending on its stored program. Embodiments ofthe RADAR detector 14 may also incorporate a user input keypad 48 orswitches. Processor 16 may be further connected to a display 50, whichmay include one or more light emitting diodes for indicating variousstatus conditions, or in a more feature-rich device, may include analphanumeric or graphical display for providing detailed information toa user. A speaker 52 may also be provided to enable processor 16 todeliver audible feedback to a user under various alert conditions.

Processor 16 may also include other interfaces (not shown), such as anODB II compliant interface, for connection to vehicle electronic systemsthat are built into the vehicle 10. Most modern vehicles are beingequipped with standardized information systems using the so-called ODBII standard interface. This standard interface is described in anarticle entitled “ODB II Diagnostics,” by Larry Carley, from Import Car,January 1997, which is hereby incorporated herein by reference.Processor 16, using the ODB II standard interface, may be able to obtainvehicle speed and other vehicle status information directly from thevehicle.

The entire bandwidth of interest is approximately 3 GHz. In someembodiments, this overall bandwidth may be effectively divided intoabout 300 channels, each approximately 10 MHz wide. In theseembodiments, a combination of changes in the first and second localoscillators 20, 22 may result in effective 10 MHz steps of the incomingRF frequency in the super heterodyne receiver 26. In other embodiments,the bandwidth may be divided into a different number of channels atdifferent bandwidths.

At each of the approximately 10 MHz steps, and as seen in the flowchart60 in FIG. 3, the following processes may occur. First, the channel isdownconverted to an intermediate frequency for processing (block 62).The ADC 40 acquires 1024 samples of data (block 64) to create a digitalsnapshot of the data in some embodiments, though other numbers ofsamples may also be used. Next, an FFT processor 42 running undercontrol of processor 16 converts the sampled data from the time domainto the frequency domain (block 66). Then, the new frequency data may beaveraged together with several previous scans/snap shots from the samechannel (block 68) to assist in reducing peak-to-peak noise variations.This process effectively reduces noise floor, and improves resultantsensitivity. However, the more averaging is applied to a portion ofspectrum—the longer it takes to complete the analysis. Therefore, inorder to detect weak signals of longer duration, it is appropriate toapply a greater amount of averaging; however, for stronger signals ofshort duration, less averaging should be applied, in order to maintainfast response. To assist in faster response times, as set forth above,the averaging may be accomplished using multiple averaging enginesconcurrently performing analysis of the frequency data. Usage ofparallel digital pipelines of the FPGA 46 may assist in implementing theconcurrent processing to achieve both speed and sensitivity, such asthrough implementation of several averaging engines running in parallel.As a result, short duration but stronger signals (such as POP) may bedetected at the output of the X1 or X8 averaging engines, and at thesame time, weak signals may also be detected at the output of the X64averaging engine. (X1, X8 and X64 averaging amounts are just onepossible scheme of distribution of averaging for a particularembodiment. Other embodiments may employ other distributions ofaverages). Finally, an amplitude of each frequency component in thespectrum is analyzed and any signals present in the spectrum areidentified (block 70). Fully digital processing, executing in thefrequency domain may assist in producing spectrum snap-shots of largeranges of bandwidth in the spectrum of interest. This may then providean opportunity for a digital processor to use pattern-recognitiontechniques to analyze and detect specific types of radar sources in someembodiments. For example, park-assist systems or automatic cruisecontrol radar systems employed in certain cars may generatefalse-alarms, unless the source of the signal is properly recognized,based on specific frequency components in the signal, and their specificrelation to one another, as determined by high speed DSP spectralanalysis of the received signal.

At the completion of the analysis, the next channel is analyzed. Ifthere is another channel to analyze (“Yes” branch of decision block 72),then the processor adjusts the frequencies of the first and second LOs20, 22 (block 74) and the process continues at block 62. If there are nofurther channels (“No” branch of decision block 72), then thefrequencies of the first and second LOs 20, 22 are reset to the basefrequency of the region of interest (block 76) and the process continuesat block 62.

The following examines potential capabilities of this system in terms offinal sensitivity as well as requirements of processing time andimplementation costs. Graph 80 in FIG. 4 illustrates a sample of whatthe frequency response data may look like. The broad hill 82 of curve 84represents the channel bandwidth and the peak 86 in the center is asignal to be detected. In some embodiments, a detection scheme mayemploy a threshold placed just above the highest noise peak in thespectrum. The sensitivity of the system many be affected by manyfactors, two of which include bandwidth and peak-to-peak variation. Thefirst factor is the final system bandwidth. It is possible to lower theabsolute (average) noise floor of the system by reducing final systembandwidth.

The final bandwidth of a sampled system depends on the sampling rate andthe number of samples:

$\begin{matrix}{{BW} = \frac{F_{s}}{N}} & (1)\end{matrix}$

BW is also the resolution or bin size of the frequency responsecalculated using Fourier Transform. For example, 1024 points acquired at32.5 MHz rate produce 31.7 kHz final bandwidth. As seen in FIG. 5, withonly Noise source 90 connected to the input, equivalent noise power wasmeasured using Noise Figure Meter 92 as 103.3 dBm (A) above absolutenoise floor in a 1 MHz (B₁) bandwidth. A 1024 point FFT 42 calculated ona signal sampled at 100 MHz should yield a 97.7 kHz (B₂) finalbandwidth. Therefore the final noise floor due to FFT should be reducedto:

$F = {{{- 114} + A - {10 \times {\log( \frac{B_{1}}{B_{2}} )}}} = {{- 20.8}\mspace{14mu}{dBm}}}$

where the constant −114 is the thermal noise power in dBm measured inthe 1 MHz bandwidth.

A signal was applied in the center of filter passband having anamplitude of 6 dB higher than F and 32 FFT results were averagedtogether. The graph 100 in FIG. 6 illustrates these results. The curve102 does show a signal 104 approximately 6 dB above average noise floor,therefore the bandwidth reduction due to FFT is in fact what waspredicted above.

In order to estimate system sensitivity it is convenient to compare thissystem to characteristics of the existing detectors. Some existingdetector units are able to detect approximately 0 dB signal-to-noise(“S/N”) ratio having final bandwidth of 400 kHz. Therefore thesensitivity improvement in dB considering only bandwidth reduction alonewould be:

${improvement} = {10 \times {\log( \frac{400\mspace{14mu}{kHz}}{BW} )}}$

In this case, 512 samples would make approximately an 8 dB sensitivityimprovement over existing detectors. Using 1024 samples would yieldapproximately an 11 dB improvement and 2048 samples would yieldapproximately a 14 dB improvement.

The second factor is the peak-to-peak variation in the noise floor. Ascan be seen below, averaging several consecutive frequency scans mayassist in reducing this variation. To test this theory, a broadbandnoise source was connected to the input of the evaluation board forNational Semiconductor's ADC08100 A/D converter. A converter running at100 MHz captured 64 batches of time domain data at 1024 samples each. AnFFT was performed on the captured data creating 64 frequency responsebatches. The frequency data was then averaged together in severalconfigurations (0, 2, 4, 8, 16, 32, and 64). These results for noaveraging, 8 averages, and 64 averages may be found in the graphs110-114 in FIGS. 7A-7C. For each configuration plotted in graphs 110-114in FIGS. 7A-7C, a histogram of sample variations was also plotted ingraphs 120-124 in FIGS. 8A-8C. As the number of averages increases, thesamples get nearer to the true average noise value. For example, as seenin the table in FIG. 9, after 8 averages, 98% of all samples will liewithin ±4.5 dB (9 dB range) of the true average value. Thus averagingconsecutive frequency scans assists in reducing any peak-to-peakvariation in the noise floor.

The table in FIG. 10 summarizes the combination of both factors—systembandwidth and peak-to-peak variation—that have been shown to affectfinal sensitivity of the system. The actual numbers were additionallydegraded by 2 dB to allow for a “safety factor” in setting a thresholdabove noisy spectrum. The numbers in the body of the table represent achange in sensitivity (in dB) compared to earlier model detectors. Inthis table, a ‘-’ means a degradation in sensitivity, and a ‘+’ means animprovement in sensitivity.

In order to determine any improvements in sensitivities, 1024 samplesand 8 averages were considered. As illustrated above, the noise floordrops due to bandwidth alone by approximately 11 dB when compared toearlier units. As seen in the table in FIG. 9, after 8 averages almost100% of samples will lie within ±6 dB (12 dB range) of the true averagevalue. Therefore, when setting the threshold value for noisedetermination, the threshold should be placed 6 dB above average noisefloor 130 plus 2 dB safety factor as seen in FIGS. 4 and 6. Thus, thesensitivity improvement for 1024 samples and 8 averages is: 11 dB−6 dB−2dB=3 dB.

The threshold is set just above the noise floor 130, such that anysignal of interest occurring in spectrum should cross the threshold andproduce an alarm condition. This threshold, in some embodiments, may begenerated as a self-adapting threshold, to envelop any unevenfluctuations in the noise floor 130, maximizing the effectiveness of thedetection method. This dynamic threshold may slowly and constantly beadjusted during the working of the detector in order to compensate forchanges in the parameters of the system due to temperature, aging, etc.

Another factor that may affect actual sensitivity of the system is anincoming signal or LO drift or jitter. For example if the signal driftsacross two FFT bins during a complete averaging cycle, then the heightof the peak in the frequency response may be lower by as much as 3 dBcompared to what it would have been if no drift had occurred. If thesignal drifts across four FFT bins, then the peak may be down by as muchas 6 dB, etc. But, the fewer number of averages taken in the cycle, theless time it takes for detection, and thus the smaller signal driftwould be.

A synthesized local oscillator's drift is generally due to a referencecrystal temperature instability, which typically changes very slowly andthus does not greatly affect sensitivity. The phase noise of theoscillator is also a fraction of a kilohertz, well below the FFT binsize. The incoming signal, however, is usually far less stable. In manycases RADARs have gun oscillators as their sources because they aretypically powerful and generally have low phase noise. However, thesegun oscillators drift significantly, especially immediately after beingturned on. For example, a typical X-band gun oscillator, upon power upat room temperature, can drift as much as 400 kHz in the first second.But, after about three seconds the drift virtually stops.

During a complete detector sweep, lasting for example about 300 ms, anincoming signal can drift approximately 200 kHz, which is about 6-7 binsfor a bin size of about 31.7 kHz. In this situation, the overalleffective sensitivity may be reduced by as much as 8 dB. However, if theincoming signal is not too weak as to be detected at the limits ofsensitivity, then the signal may be detected much faster than after 8averages and may not drift far enough to degrade “instant-on”performance. But, considering the worst case scenario, a typical gunoscillator drifts only about 20 Hz in the time it takes to do one scanof one channel with no averaging (approximately 30 μs). This is verysmall compared to the FFT bin size to make any significant difference onperformance.

The performance of the embodiments of the invention depends in part onthe processing power of the DSP chip. Several processors were found tobe capable of processing a 1024-point FFT algorithm in about 50-60 μs atfairly low cost. Two examples are the TMS320C6204 from Texas Instrumentsand the ADSP-21532 “Blackfin” from Analog Devices. In general, the mainportion of total time necessary to run a complete processing chain willlikely be consumed by the FFT routine (approximately 60 μs). Extrapostprocessing and averaging of data for a DSP running at 200 MHzapproximately adds another 20 μs. Transfer of data from A/D converter toDSP (approximately 32 μs) may be accomplished in the background usingDMA and therefore need not be taken into the account.

Dividing total scanning range of about 3 GHz into approximately 10 MHzsteps results in 300 channels to scan. Considering the case when 8averages are taken at each step, the total processing time for theentire scanning range amounts to:(60+20) μs×8avg×300 steps=192 ms  (4)

This is faster than scans from contemporary detectors that complete inabout 300 ms. In addition to be able to scan faster, as establishedabove, embodiments of the invention also provide a 3 dB improvement insensitivity.

Analysis of a detection scheme using digital receiving technique exposesseveral advantages in using this system compared to traditional FMdemodulator detection. The example configurations of embodiments usedthroughout this disclosure produce approximately a 3 dB improvement inoverall sensitivity compared to contemporary detectors while achievingthis improvement about 30 percent faster than contemporary detectors.With a proper choice of first LO frequency it is possible to scan K andportion of the Ka band simultaneously, which should further reduceprocessing time. In case a signal is detected in this overlapped region,it may be necessary to rescan the area around the signal to identify theactual band the signal is coming from, however this process should stillbe much faster than scanning K and Ka bands separately. Becausesensitivity and speed are under software control, it is possible toredistribute different levels of performance to different bands ofinterest. For example certain bands may be scanned with higher number ofaverages than others thus achieving even better sensitivity and/or speedlevels.

In general, the digital architecture of the embodiments of the detectorassists in balancing between sensitivity and response time. This balancemay also be dynamically shifted depending on situation providing greaterflexibility in control of the performance.

Contemporary RADAR detectors typically sweep their first LO linearly andslowly in order to scan the entire bandwidth of interest. However, theLO signal usually leaks into the environment, allowing other devices(RADAR-detector detectors) to identify the presence of this detector,which is can be undesirable. But, in the fully digital platform, thefirst LO is fixed by a phase-lock-loop, setting its frequency in stepsin order to cover the entire spectrum. At each step, the oscillator'sfrequency is fixed for a very short duration (typically 25 micro sec)while the channel is being digitized. Given the digital nature of thisprocess, such steps need not be performed in sequential order, as longas all required frequency channels are covered. The order of thesechannels may be made pseudo-random (predetermined fixed non-sequentialsequence), which may assist in making detection and identification ofthis device more difficult. The seemingly random jumping of the firstoscillator's frequency will effectively spread its radiated energy overa wide band, making the detector 14 harder to detect. Some embodimentsof the detector 14 may also utilize several pseudo-random patterns,cycling through each pattern, again making the detection andidentification of the device more difficult. Other embodiments mayemploy a fully random order of the channels. In these embodiments,statistics may be utilized to determine how often a particular channelis visited, in order to ensure that each channel gets visitedperiodically.

While the present invention has been illustrated by a description of oneor more embodiments thereof and while these embodiments have beendescribed in considerable detail, they are not intended to restrict orin any way limit the scope of the appended claims to such detail.Additional advantages and modifications will readily appear to thoseskilled in the art. The invention in its broader aspects is thereforenot limited to the specific details, representative apparatus andmethod, and illustrative examples shown and described. Accordingly,departures may be made from such details without departing from thescope of the general inventive concept.

What is claimed is:
 1. A method of detecting a RADAR signal, comprising:receiving RADAR signal in a police RADAR frequency range into aheterodyne receiver utilizing a local oscillator, wherein the policeRADAR frequency range is divided into a plurality of equally widechannels; shifting a first channel of the RADAR signal to anintermediate frequency (IF) utilizing the heterodyne receiver; digitallyprocessing the received RADAR channel data via an analog-to-dcconverter; analyzing the processed channel data under control of aprocessor to identify an apparent police originated RADAR signal in theRADAR channel data in the frequency range; advancing the frequency rangeof the heterodyne receiver to a next channel of the plurality ofchannels, wherein the frequency range of the next channel of theplurality of channels is nonsequential with the frequency range of thefirst channel; and repeating the steps of receiving, processing, andanalyzing for the next channel of the plurality of channels.
 2. Themethod of claim 1, wherein the frequency range encompasses the X, K, andKa RF bands.
 3. The method of claim 1, wherein digitally processing thereceived RADAR channel data comprises: concurrently averaging digitallyconverted samples of the RADAR channel data with digitally convertedsamples from previously received RADAR channel data, wherein theconcurrent averaging is performed in parallel utilizing multipleaveraging engines.
 4. The method of claim 1, wherein analyzing theprocessed channel data to identify a signal in the RADAR channel data inthe frequency range comprises: comparing samples to a predeterminedthreshold.
 5. The method of claim 4, wherein the threshold is a dynamicself-adapting threshold.
 6. The method of claim 5, wherein the thresholdadapts to compensate for temperature variations.
 7. The method of claim1, wherein a pseudo-random channel pattern is utilized for advancing tothe next channel of the plurality of channels.
 8. The method of claim 1,wherein the next channel of the plurality of channels is randomlyselected from the plurality of channels.
 9. The method of claim 8,further comprising: statistically analyzing a number of times a channelof the plurality of channels has been analyzed to ensure each channel ofthe plurality of channels is periodically analyzed.
 10. An apparatus fordetecting a RADAR signal, comprising: a receiver; a processor; and anaverager module, wherein the processor is in communication with thereceiver and the averager module, and the processor is configured to: i.receive via the receiver RADAR channel data in a frequency range,wherein the frequency range is divided into a plurality of equally widechannels; ii. digitally process the received RADAR channel data; iii.analyze the processed channel data to identify a signal in the RADARchannel data in the frequency range; iv. advance the frequency range toa next channel of the plurality of channels, wherein the frequency rangeof the next channel of the plurality of channels is nonsequential withthe frequency range of the first channel; and v. repeat the steps ofreceiving, processing, and analyzing for the next channel of theplurality of channels.
 11. The apparatus of claim 10, wherein thereceiver comprises: a RF antenna; a plurality of local oscillators; anda band pass filter, wherein the plurality of local oscillators selectbands of frequency in the frequency range under control of theprocessor.
 12. The apparatus of claim 10, wherein the processordigitally processes the received RADAR channel data by: concurrentlyaveraging in the averager module digitally converted samples of theRADAR channel data with digitally converted samples from previouslyreceived RADAR channel data, wherein the concurrent averaging isperformed in parallel utilizing multiple averaging engines within theaverager module.
 13. The apparatus of claim 10, wherein the processor isconfigured to analyze the processed channel data to identify a signal inthe RADAR channel data in the frequency range by: comparing samples to apredetermined threshold.
 14. The apparatus of claim 13, wherein thethreshold is a dynamic self-adapting threshold.
 15. The apparatus ofclaim 14, wherein the processor is further configured to adapt thethreshold to compensate for temperature variations.
 16. The apparatus ofclaim 10, wherein a pseudo-random channel pattern is utilized by theprocessor for advancing to the next channel of the plurality ofchannels.
 17. The apparatus of claim 10, wherein the next channel of theplurality of channels is randomly selected by the processor from theplurality of channels.
 18. The apparatus of claim 17, wherein theprocessor is further configured to: statistically analyze a number oftimes a channel of the plurality of channels has been analyzed to ensureeach channel of the plurality of channels is periodically analyzed. 19.The apparatus of claim 10, further comprising: a user interface.
 20. Theapparatus of claim 19, wherein the user interface comprises: a speaker;a display; and a keypad.